Multifunctional Self-Powered Sensors Integrated on a Robot Hand for Detecting Temperature–Pressure Stimuli and Recognizing Objects

• Published in: ACS applied materials & interfaces Vol. 16; no. 40; pp. 54475 - 54484
• Main Authors: Qi, Xiangyu, Wang, Linglu, Li, Chuanbo, Wang, Yang
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 09.10.2024
• Subjects: energy; Functional Nanostructured Materials (including low-D carbon); heat tolerance; temperature; object recognition; triboelectric nanogenerators; machine learning methods; pressure and temperature sensing; self-powered sensor
• ISSN: 1944-8244; 1944-8252; 1944-8252
• DOI: 10.1021/acsami.4c12062

Tactile sensing, especially pressure and temperature recognition, is crucial for both humans and robots in identifying objects. The general solutions, which use piezoresistive, capacitive, and thermal resistance effects, are usually subject to single-mode sensing and an energy supply. Here, we propose a multimode self-powered sensor. The sensor can respond to pressure and temperature stimuli using triboelectric and thermoelectric effects. Furthermore, we developed a sensing system comprising sensors, a deep learning block, and a smart board. The deep learning model can fuse features of triboelectric and thermoelectric signals, enabling a high accuracy of 99.8% in recognizing ten objects. This method may provide the future design of self-powered sensors for object recognition in robotics.